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Optimization & Theory

43,292 papers (3 classified directly here)

Subtopics · a paper can sit in several, so these overlap

Optimization (17,731) Learning Theory (6,809) Bayesian Inference (6,267) Theory (5,579) Statistical Learning (4,564) Neural Network Optimization (4,155) Stochastic Processes (2,948) Stochastic Methods (1,283) Loss Functions (1,220) Distributed Learning (1,202) Online Algorithms (1,013) Statistics (822) Generalization (376) Information Theory (370) Sample Complexity (282) Sparse Optimization (241) Game Theory (151) Convex Optimization (132) Optimal Transport (104) Robust Optimization (84) Distributed Optimization (73) Approximation Algorithms (33)

Papers per year

1
52
352
828
3,646
5,854
2000
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Papers (including subtopics)

Compositional abstraction error and a category of causal models UAI 2021 Compositional Modeling of Nonlinear Dynamical Systems with ODE-based Random Features NeurIPS 2021 Compressed Maximum Likelihood ICML 2021 Compression, Transduction, and Creation: A Unified Framework for Evaluating Natural Language Generation EMNLP 2021 Computational Analyses of the Electoral College: Campaigning Is Hard But Approximately Manageable AAAI 2021 Computationally Efficient Wasserstein Loss for Structured Labels EACL 2021 Computational Separation Between Convolutional and Fully-Connected Networks ICLR 2021 Computing Quantal Stackelberg Equilibrium in Extensive-Form Games AAAI 2021 Concentration inequalities under sub-Gaussian and sub-exponential conditions NeurIPS 2021 Concentration of Non-Isotropic Random Tensors with Applications to Learning and Empirical Risk Minimization COLT 2021 CondenseNet V2: Sparse Feature Reactivation for Deep Networks CVPR 2021 Conditional Bures Metric for Domain Adaptation CVPR 2021 Conditionally Parameterized, Discretization-Aware Neural Networks for Mesh-Based Modeling of Physical Systems NeurIPS 2021 Conditional Poisson Stochastic Beams EMNLP 2021 Conditional probing: measuring usable information beyond a baseline EMNLP 2021 Conditional Temporal Neural Processes with Covariance Loss ICML 2021 Conditioning Sparse Variational Gaussian Processes for Online Decision-making NeurIPS 2021 Condition number bounds for causal inference UAI 2021 Condorcet Relaxation In Spatial Voting AAAI 2021 Confidence-Budget Matching for Sequential Budgeted Learning ICML 2021 Confidence Intervals for ASR-Based TTS Evaluation Interspeech 2021 Confident Off-Policy Evaluation and Selection through Self-Normalized Importance Weighting AISTATS 2021 Conflict-Averse Gradient Descent for Multi-task learning NeurIPS 2021 Conflicting Bundles: Adapting Architectures Towards the Improved Training of Deep Neural Networks WACV 2021 Conformal Bayesian Computation NeurIPS 2021